On real-time capacity of event-driven data-gathering sensor networks

Abstract—Network capacity is a critical feature of wireless ad hoc and sensor networks. It is particularly challenging to determine network capacity when combined with other perfor-mance objectives such as timeliness. This paper investigates real-time capacity for event-driven data-gathering sensor networks with unbalanced many-to-one traffic patterns. First, we compute the average allowable throughputs of nodes for a given event distribution, based on which we then leverage results of queuing theory to estimate the per-hop delays. We develop a new slack time distribution scheme for unbalanced many-to-one traffic patterns, and prove it as optimal in terms of the per-hop success probability. Here the per-hop success probability is defined as the probability for a packet to meet its sub-deadlines at each hop. Finally, we define and analyze the network-wide real-time ca-pacity, i.e., given a threshold for the per-hop success probability, how much data (in bit per second) can be delivered to the sink node meeting their deadlines. For all these research results, we provide some application scenarios, including configuring packet deadlines or verifying a specific configuration, setting a packet’s priority for dynamic scheduling, and trading the reliability of real-time data delivery for capacity efficiency etc. We also study two special cases of WSNs, the chain model and the continuous model. Our slack distribution scheme yields consistent or similar results for these special cases as that of past works, but is more adaptive by supporting more generic cases. I